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                <p>Tensorflow部分知识点。<span id="more"></span> </p>
<h1 id="一、tf-app-run"><a href="#一、tf-app-run" class="headerlink" title="一、tf.app.run()"></a>一、tf.app.run()</h1><p>&emsp;&emsp;<strong>作用：</strong>主函数run会调用main，首先加载flags的参数项，然后执行main()函数，其中参数使用tf.app.flags.FLAGS定义的。<br>&emsp;&emsp;<strong>说明：</strong>1. 如果代码中的入口函数不叫main()，而是一个其他名字的函数，如main()或test(),则应该写入口tf.app.run(main)或tf.app.run(test)。如下所示：</p>
<pre class="line-numbers language-python"><code class="language-python"><span class="token keyword">def</span> <span class="token function">main</span><span class="token punctuation">(</span>_<span class="token punctuation">)</span><span class="token punctuation">:</span>
    train<span class="token punctuation">(</span><span class="token punctuation">)</span>

<span class="token keyword">if</span> __name__ <span class="token operator">==</span> <span class="token string">'__main__'</span><span class="token punctuation">:</span>
    tf<span class="token punctuation">.</span>app<span class="token punctuation">.</span>run<span class="token punctuation">(</span>main<span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span><span></span></span></code></pre>
<h1 id="二、def-init-（）初始化"><a href="#二、def-init-（）初始化" class="headerlink" title="二、def _init_（）初始化"></a>二、def _init_（）初始化</h1><p>&emsp;&emsp;作为典型的面向对象的语言，python中<strong>类</strong>的<strong>定义和使用</strong>是必不可少的。常见的类的定义有两种：</p>
<h5 id="emsp-emsp-1-def-init-self"><a href="#emsp-emsp-1-def-init-self" class="headerlink" title="&emsp;&emsp;1. def init (self)"></a>&emsp;&emsp;1. def init (self)</h5><pre class="line-numbers language-python"><code class="language-python"><span class="token keyword">class</span> <span class="token class-name">read_properties</span><span class="token punctuation">:</span>
    <span class="token keyword">def</span> <span class="token function">__init__</span><span class="token punctuation">(</span>self<span class="token punctuation">)</span><span class="token punctuation">:</span> <span class="token comment" spellcheck="true"># 也可以是其他的，如def _init_(me),后面的self改为me即可。</span>
        self<span class="token punctuation">.</span>name <span class="token operator">=</span> None
        self<span class="token punctuation">.</span>grade <span class="token operator">=</span> None
    <span class="token keyword">def</span> <span class="token function">print_grade</span><span class="token punctuation">(</span>self<span class="token punctuation">)</span><span class="token punctuation">:</span>
        <span class="token keyword">print</span><span class="token punctuation">(</span><span class="token string">"%s grade is %s"</span> <span class="token operator">%</span> <span class="token punctuation">(</span>self<span class="token punctuation">.</span>name<span class="token punctuation">,</span>self<span class="token punctuation">.</span>grade<span class="token punctuation">)</span><span class="token punctuation">)</span>

s1 <span class="token operator">=</span> read_properties<span class="token punctuation">(</span><span class="token punctuation">)</span>   <span class="token comment" spellcheck="true"># 创建对象</span>
s1<span class="token punctuation">.</span>grade <span class="token operator">=</span><span class="token string">'100'</span>
s1<span class="token punctuation">.</span>name <span class="token operator">=</span> <span class="token string">"chen"</span>

s1<span class="token punctuation">.</span>print_grade<span class="token punctuation">(</span><span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;这种形式中，只有一个self，在方法的内部，包含name、grade两个属性，也可创建多个属性。之后创建一个实例s1，根据预先定义好的规则，包含具体数据，如上述的self.grade和self.name。在这种形式中，先进行实例化，再对属性赋值。<br><img src="/Images/NERRUN/image-20210330203016295.png" alt="image-20210330203016295"></p>
<h5 id="emsp-emsp-2-def-init-self-name-grade"><a href="#emsp-emsp-2-def-init-self-name-grade" class="headerlink" title="&emsp;&emsp;2. def init(self,name,grade)"></a>&emsp;&emsp;2. def init(self,name,grade)</h5><pre class="line-numbers language-python"><code class="language-python"><span class="token keyword">class</span> <span class="token class-name">read</span><span class="token punctuation">:</span>
    <span class="token keyword">def</span> <span class="token function">__init__</span><span class="token punctuation">(</span>self<span class="token punctuation">,</span>name<span class="token punctuation">,</span>grade<span class="token punctuation">)</span><span class="token punctuation">:</span> <span class="token comment" spellcheck="true"># 也可以是其他的，如def _init_(me)</span>
        self<span class="token punctuation">.</span>Name <span class="token operator">=</span> name
        self<span class="token punctuation">.</span>Grade <span class="token operator">=</span> grade
    <span class="token keyword">def</span> <span class="token function">print_grade</span><span class="token punctuation">(</span>self<span class="token punctuation">)</span><span class="token punctuation">:</span>
        <span class="token keyword">print</span><span class="token punctuation">(</span><span class="token string">"%s grade is %s"</span> <span class="token operator">%</span> <span class="token punctuation">(</span>self<span class="token punctuation">.</span>Name<span class="token punctuation">,</span>self<span class="token punctuation">.</span>Grade<span class="token punctuation">)</span><span class="token punctuation">)</span>
        
s1 <span class="token operator">=</span> read<span class="token punctuation">(</span><span class="token string">'chen'</span><span class="token punctuation">,</span> <span class="token number">100</span><span class="token punctuation">)</span>   <span class="token comment" spellcheck="true"># 创建对象</span>
s1<span class="token punctuation">.</span>print_grade<span class="token punctuation">(</span><span class="token punctuation">)</span>
<span class="token keyword">print</span><span class="token punctuation">(</span>s1<span class="token punctuation">.</span>Name<span class="token punctuation">)</span>   <span class="token comment" spellcheck="true"># 直接进行输出</span>
<span class="token keyword">print</span><span class="token punctuation">(</span>s1<span class="token punctuation">.</span>grade<span class="token punctuation">)</span>   <span class="token comment" spellcheck="true"># 直接进行输出</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;上述示例中，共有三个参数，self是创建类的实例的时候被创建的实例本身（示例中为s1），习惯称为self，也可为其他的如me，后续将self改为me即可。执行实例化的过程会变为s1(name,grade)，新建的实例本身，连带其中的参数，一并传入init函数中。其中self.Name = name，是为了区分前后两个是不同的东西，等号左边的Name是实例的属性，后面的name是方法init的参数。<br><img src="/Images/NERRUN/image-20210330203056225.png" alt="image-20210330203056225"></p>
<h1 id="三、strip-、get-方法"><a href="#三、strip-、get-方法" class="headerlink" title="三、strip()、get()方法"></a>三、strip()、get()方法</h1><p>&emsp;&emsp;<strong>python strip()方法</strong>用于移除字符串头尾指定的字符（默认为空格或换行符）或字符序列。只能删除开头或是结尾的字符，不能删除中间部分的字符。示例：str.strip([chars])。</p>
<pre class="line-numbers language-python"><code class="language-python">str <span class="token operator">=</span> <span class="token string">"123filename = data/vecs.lc.over.txt\n"</span>
<span class="token keyword">print</span><span class="token punctuation">(</span>str<span class="token punctuation">.</span>strip<span class="token punctuation">(</span><span class="token string">"123"</span><span class="token punctuation">)</span><span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;输出结果：<br>&emsp;&emsp;<img src="/Images/NERRUN/image-20210330203140183.png" alt="image-20210330203140183"><br>&emsp;&emsp;<strong>python get()函数</strong>的使用方法：</p>
<pre class="line-numbers language-python"><code class="language-python">dict <span class="token operator">=</span> <span class="token punctuation">{</span><span class="token string">'name'</span><span class="token punctuation">:</span><span class="token string">'chen'</span><span class="token punctuation">,</span><span class="token string">'Age'</span><span class="token punctuation">:</span><span class="token number">27</span><span class="token punctuation">}</span>
<span class="token keyword">print</span><span class="token punctuation">(</span><span class="token string">"Value：%s"</span><span class="token operator">%</span> dict<span class="token punctuation">.</span>get<span class="token punctuation">(</span><span class="token string">'Age'</span><span class="token punctuation">)</span><span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;输出结果：<br>&emsp;<img src="/Images/NERRUN/image-20210330203312713.png" alt="image-20210330203312713"></p>
<h1 id="四、-t-n"><a href="#四、-t-n" class="headerlink" title="四、\t  \n"></a>四、\t  \n</h1><p>&emsp;&emsp;\t是水平制表符，即TAB键，一般相当于四个空格，类似于文档中的缩进功能。\n是换行符。</p>
<pre class="line-numbers language-python"><code class="language-python"><span class="token keyword">print</span><span class="token punctuation">(</span><span class="token string">"\t你好"</span><span class="token punctuation">)</span>
<span class="token keyword">print</span><span class="token punctuation">(</span><span class="token string">"\n你好\n你在哪儿"</span><span class="token punctuation">)</span>
<span class="token keyword">print</span><span class="token punctuation">(</span><span class="token string">"你好\n\t我在\n\t广州"</span><span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;输出结果：<br><img src="/Images/NERRUN/image-20210330202913984.png" alt="image-20210330202913984"></p>
<h1 id="五、extend-函数、append-函数"><a href="#五、extend-函数、append-函数" class="headerlink" title="五、extend()函数、append()函数"></a>五、extend()函数、append()函数</h1><p>&emsp;&emsp;<strong>extend()函数</strong>用于在列表末尾一次性追加<strong>另一个序列中的多个值</strong>（用新列表扩展原来的列表）。该方法没有返回值，但会在已存在的列表中添加新的列表内容。</p>
<pre class="line-numbers language-python"><code class="language-python">list <span class="token operator">=</span> <span class="token punctuation">[</span><span class="token string">'01'</span><span class="token punctuation">,</span><span class="token string">'李四'</span><span class="token punctuation">,</span><span class="token string">'lisi'</span><span class="token punctuation">]</span>
list<span class="token punctuation">.</span>extend<span class="token punctuation">(</span><span class="token punctuation">[</span><span class="token string">'02'</span><span class="token punctuation">,</span><span class="token string">'陈静'</span><span class="token punctuation">,</span><span class="token string">'chenjing'</span><span class="token punctuation">]</span><span class="token punctuation">)</span>
<span class="token keyword">print</span><span class="token punctuation">(</span>list<span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;输出结果：<br><img src="/Images/NERRUN/image-20210330202813959.png" alt="image-20210330202813959"></p>
<p>&emsp;&emsp;<strong>append()函数</strong>：是向列表中<strong>添加一个对象</strong></p>
<pre class="line-numbers language-python"><code class="language-python">list1 <span class="token operator">=</span> <span class="token punctuation">[</span><span class="token string">'01'</span><span class="token punctuation">,</span><span class="token string">'李四'</span><span class="token punctuation">,</span><span class="token string">'lisi'</span><span class="token punctuation">]</span>
list1<span class="token punctuation">.</span>append<span class="token punctuation">(</span><span class="token punctuation">[</span><span class="token string">'02'</span><span class="token punctuation">,</span><span class="token string">'陈静'</span><span class="token punctuation">,</span><span class="token string">'chenjing'</span><span class="token punctuation">]</span><span class="token punctuation">)</span>
<span class="token keyword">print</span><span class="token punctuation">(</span>list1<span class="token punctuation">)</span>

list1 <span class="token operator">=</span> <span class="token punctuation">[</span><span class="token string">'01'</span><span class="token punctuation">,</span><span class="token string">'李四'</span><span class="token punctuation">,</span><span class="token string">'lisi'</span><span class="token punctuation">]</span>
list1<span class="token punctuation">.</span>append<span class="token punctuation">(</span><span class="token string">'02'</span><span class="token punctuation">)</span>
<span class="token keyword">print</span><span class="token punctuation">(</span>list1<span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;输出结果:<br><img src="/Images/NERRUN/image-20210331205833750.png" alt="image-20210331205833750"><img src="/Images/NERRUN/image-20210331205939280.png" alt="image-20210331205939280"></p>
<h1 id="六、set-方法"><a href="#六、set-方法" class="headerlink" title="六、set()方法"></a>六、set()方法</h1><p>&emsp;&emsp;1、set最主要的功能是寻找一个句子或列表中不同的元素。当sentence是一个字符串时，不是将其作为单个单词分割，而是将其分割成了每一个字符。</p>
<pre class="line-numbers language-python"><code class="language-python">chars <span class="token operator">=</span> <span class="token punctuation">[</span><span class="token string">'M'</span><span class="token punctuation">,</span><span class="token string">'R'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'C'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">]</span>
<span class="token keyword">print</span><span class="token punctuation">(</span>set<span class="token punctuation">(</span>chars<span class="token punctuation">)</span><span class="token punctuation">)</span>
chars <span class="token operator">=</span> <span class="token punctuation">[</span><span class="token string">'This'</span><span class="token punctuation">,</span><span class="token string">'is'</span><span class="token punctuation">,</span><span class="token string">'my'</span><span class="token punctuation">,</span><span class="token string">'home'</span><span class="token punctuation">,</span><span class="token string">'is'</span><span class="token punctuation">]</span>
<span class="token keyword">print</span><span class="token punctuation">(</span>set<span class="token punctuation">(</span>chars<span class="token punctuation">)</span><span class="token punctuation">)</span>
sentence <span class="token operator">=</span> <span class="token string">'Welcome to China!'</span>
<span class="token keyword">print</span><span class="token punctuation">(</span>set<span class="token punctuation">(</span>sentence<span class="token punctuation">)</span><span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;输出的结果为：<br><img src="/Images/NERRUN/image-20210331083715793.png" alt="image-20210331083715793"><br>&emsp;&emsp;<strong>2、添加元素：</strong>使用add就能添加某个元素，但不是每一个都能添加，如列表。<strong>添加只能添加单个元素而不是像列表这种复合对象。</strong></p>
<pre class="line-numbers language-python"><code class="language-python">chars <span class="token operator">=</span> <span class="token punctuation">[</span><span class="token string">'M'</span><span class="token punctuation">,</span><span class="token string">'R'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'C'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">]</span>
char <span class="token operator">=</span> set<span class="token punctuation">(</span>chars<span class="token punctuation">)</span>
char<span class="token punctuation">.</span>add<span class="token punctuation">(</span><span class="token string">'F'</span><span class="token punctuation">)</span>
<span class="token keyword">print</span><span class="token punctuation">(</span>char<span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;输出的结果是：</p>
<p><img src="/Images/NERRUN/image-20210331090004416.png" alt="image-20210331090004416"></p>
<p>&emsp;&emsp;<strong>3、清除元素和清空set</strong>：清除一个元素可以用remove或者discard，而清除全部可以用clear。<br>&emsp;&emsp;&emsp;&emsp;<strong>3.1 清除元素</strong></p>
<pre class="line-numbers language-python"><code class="language-python">chars <span class="token operator">=</span> <span class="token punctuation">[</span><span class="token string">'M'</span><span class="token punctuation">,</span><span class="token string">'R'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'C'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">]</span>
char <span class="token operator">=</span> set<span class="token punctuation">(</span>chars<span class="token punctuation">)</span>
char<span class="token punctuation">.</span>remove<span class="token punctuation">(</span><span class="token string">'A'</span><span class="token punctuation">)</span>
<span class="token keyword">print</span><span class="token punctuation">(</span>char<span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;输出的结果是：<br><img src="/Images/NERRUN/image-20210331090421855.png" alt="image-20210331090421855"><br>&emsp;&emsp;&emsp;&emsp;<strong>3.2 清空元素</strong></p>
<pre class="line-numbers language-python"><code class="language-python">chars <span class="token operator">=</span> <span class="token punctuation">[</span><span class="token string">'M'</span><span class="token punctuation">,</span><span class="token string">'R'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'C'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">,</span><span class="token string">'A'</span><span class="token punctuation">]</span>
char <span class="token operator">=</span> set<span class="token punctuation">(</span>chars<span class="token punctuation">)</span>
char<span class="token punctuation">.</span>clear<span class="token punctuation">(</span><span class="token punctuation">)</span>
<span class="token keyword">print</span><span class="token punctuation">(</span>char<span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;输出的结果为：<br><img src="/Images/NERRUN/image-20210331090709371.png" alt="image-20210331090709371"></p>
<h1 id="七、list-方法"><a href="#七、list-方法" class="headerlink" title="七、list()方法"></a>七、list()方法</h1><p>&emsp;&emsp;list()方法是将元组或字符串转换为<strong>列表</strong>。元组与列表是非常相似的，<strong>区别</strong>在于元组的元素值不能修改，元组是放在括号中，列表是放于方括号中。</p>
<pre class="line-numbers language-python"><code class="language-python">atuple<span class="token operator">=</span><span class="token punctuation">(</span><span class="token number">123</span><span class="token punctuation">,</span><span class="token string">'this'</span><span class="token punctuation">,</span><span class="token string">'is'</span><span class="token punctuation">,</span><span class="token string">'my'</span><span class="token punctuation">,</span><span class="token string">'home'</span><span class="token punctuation">)</span>
<span class="token keyword">print</span><span class="token punctuation">(</span><span class="token string">"atuple:"</span><span class="token punctuation">,</span>list<span class="token punctuation">(</span>atuple<span class="token punctuation">)</span><span class="token punctuation">)</span>

sentence <span class="token operator">=</span> <span class="token string">'Welcome to China!'</span>
<span class="token keyword">print</span><span class="token punctuation">(</span><span class="token string">"sentence:"</span><span class="token punctuation">,</span>list<span class="token punctuation">(</span>sentence<span class="token punctuation">)</span><span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;输出结果为：<br><img src="/Images/NERRUN/image-20210331091329709.png" alt="image-20210331091329709"></p>
<h1 id="八、模型的加载和保存"><a href="#八、模型的加载和保存" class="headerlink" title="八、模型的加载和保存"></a>八、模型的加载和保存</h1><p>&emsp;&emsp;在机器学习中，会进行模型的训练，最常用的就是sklearn中的库，而对于训练好的模型，是要进行保存的。则会使用sklearn中的joblib模块来进行保存和加载。<br>&emsp;&emsp;<strong>一、模型的保存：</strong>job.dump(estimator,’;test.pkl’)</p>
<pre class="line-numbers language-python"><code class="language-python"><span class="token keyword">import</span> joblib
data1 <span class="token operator">=</span> <span class="token punctuation">{</span> <span class="token punctuation">.</span><span class="token punctuation">.</span><span class="token punctuation">.</span><span class="token punctuation">.</span>一堆数据 <span class="token punctuation">}</span>
joblib<span class="token punctuation">.</span>dump<span class="token punctuation">(</span>data1<span class="token punctuation">,</span><span class="token string">'../tmp/test/pkl'</span><span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;<strong>二、模型的加载：</strong>estimator = joblib.load(“test.pkl”)</p>
<pre class="line-numbers language-python"><code class="language-python">rd <span class="token operator">=</span> joblib<span class="token punctuation">.</span>load<span class="token punctuation">(</span><span class="token string">'../tmp/test/pkl'</span><span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span></span></code></pre>
<p>&emsp;&emsp;<strong>三、对pkl的理解</strong><br>&emsp;&emsp;pkl是python中的一种存储方式，可以存储为.pkl文件，是将python项目过程中用到的一些暂时变量或者需要提取咱村的字符串、列表、字典等数据保存起来。如果直接打开的话是一堆序列化的东西，正确的方式是使用pickle模块，它能将任意一个python对象转化成一系统字节，这个操作过程叫做串行化对象。该模块实现了用于序列化（以二进制的形式序列化）和反序列化（将文件中的数据解析为一个python对象）python对象结构的二进制协议。</p>
<h1 id="九、np-arange-函数"><a href="#九、np-arange-函数" class="headerlink" title="九、np.arange()函数"></a>九、np.arange()函数</h1><p>&emsp;&emsp;返回值：np.arrange()函数返回一个<strong>有终点和起点的固定步长的排列</strong>，如[1,2,3,4,5],起点是1，终点是5，步长为1。np.arange()函数的参数分为三种：<br>&emsp;&emsp;<strong>1、</strong>一个参数时，参数值为终点，起点默认值0，步长默认值为1。np.arange(3)  [0,1,2]<br>&emsp;&emsp;<strong>2、</strong>两个参数时，第一个参数为起点，第二个参数为终点，步长默认为1。np.arange(3,9) [3,4,5,6,7,8,9]<br>&emsp;&emsp;<strong>3、</strong>三个参数时，第一个参数为起点，第二个参数为终点，第三个参数为步长，其中步长支持小数点。np.arange(0,1,0.1)  [0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9]</p>
<h1 id="十、tf-set-random-seed的用法"><a href="#十、tf-set-random-seed的用法" class="headerlink" title="十、tf.set_random_seed的用法"></a>十、tf.set_random_seed的用法</h1><p>&emsp;&emsp;当在代码中使用了随机数，但希望代码在不同时间和机器上运行能得到相同的随机数，以至于能够得到相同的结果，那么就需要设置随机函数的seed参数，对应的变量可以跨session生成相同的随机数。</p>
<pre class="line-numbers language-python"><code class="language-python"><span class="token keyword">import</span> tensorflow <span class="token keyword">as</span> tf
tf<span class="token punctuation">.</span>reset_default_graph<span class="token punctuation">(</span><span class="token punctuation">)</span><span class="token comment" spellcheck="true">#函数用于清除默认图形堆栈并重置全局默认图形</span>
tf<span class="token punctuation">.</span>set_random_seed<span class="token punctuation">(</span><span class="token number">1</span><span class="token punctuation">)</span><span class="token comment" spellcheck="true">#设置全局随机种子</span>
a<span class="token operator">=</span> tf<span class="token punctuation">.</span>random_normal<span class="token punctuation">(</span><span class="token punctuation">[</span><span class="token number">1</span><span class="token punctuation">]</span><span class="token punctuation">,</span>mean<span class="token operator">=</span><span class="token number">0</span><span class="token punctuation">,</span> stddev<span class="token operator">=</span><span class="token number">1</span><span class="token punctuation">)</span>
b<span class="token operator">=</span> tf<span class="token punctuation">.</span>random_normal<span class="token punctuation">(</span><span class="token punctuation">[</span><span class="token number">1</span><span class="token punctuation">]</span><span class="token punctuation">,</span>mean<span class="token operator">=</span><span class="token number">0</span><span class="token punctuation">,</span>stddev<span class="token operator">=</span><span class="token number">1</span><span class="token punctuation">)</span>
<span class="token keyword">print</span><span class="token punctuation">(</span><span class="token string">'Session1'</span><span class="token punctuation">)</span>
<span class="token keyword">with</span> tf<span class="token punctuation">.</span>Session<span class="token punctuation">(</span><span class="token punctuation">)</span> <span class="token keyword">as</span> sess1<span class="token punctuation">:</span>
  <span class="token keyword">print</span><span class="token punctuation">(</span>sess1<span class="token punctuation">.</span>run<span class="token punctuation">(</span>a<span class="token punctuation">)</span><span class="token punctuation">)</span>
  <span class="token keyword">print</span><span class="token punctuation">(</span>sess1<span class="token punctuation">.</span>run<span class="token punctuation">(</span>a<span class="token punctuation">)</span><span class="token punctuation">)</span>
  <span class="token keyword">print</span><span class="token punctuation">(</span>sess1<span class="token punctuation">.</span>run<span class="token punctuation">(</span>b<span class="token punctuation">)</span><span class="token punctuation">)</span>
  <span class="token keyword">print</span><span class="token punctuation">(</span>sess1<span class="token punctuation">.</span>run<span class="token punctuation">(</span>b<span class="token punctuation">)</span><span class="token punctuation">)</span>

<span class="token keyword">print</span><span class="token punctuation">(</span><span class="token string">'Session2'</span><span class="token punctuation">)</span>
<span class="token keyword">with</span> tf<span class="token punctuation">.</span>Session<span class="token punctuation">(</span><span class="token punctuation">)</span> <span class="token keyword">as</span> sess2<span class="token punctuation">:</span>
  <span class="token keyword">print</span><span class="token punctuation">(</span>sess2<span class="token punctuation">.</span>run<span class="token punctuation">(</span>a<span class="token punctuation">)</span><span class="token punctuation">)</span>
  <span class="token keyword">print</span><span class="token punctuation">(</span>sess2<span class="token punctuation">.</span>run<span class="token punctuation">(</span>a<span class="token punctuation">)</span><span class="token punctuation">)</span>
  <span class="token keyword">print</span><span class="token punctuation">(</span>sess2<span class="token punctuation">.</span>run<span class="token punctuation">(</span>b<span class="token punctuation">)</span><span class="token punctuation">)</span>
  <span class="token keyword">print</span><span class="token punctuation">(</span>sess2<span class="token punctuation">.</span>run<span class="token punctuation">(</span>b<span class="token punctuation">)</span><span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;输出结果为：<br><img src="/Images/NERRUN/image-20210403154823816.png" alt="image-20210403154823816"></p>
<h1 id="十一、prettytable库打印表格美化输出功能"><a href="#十一、prettytable库打印表格美化输出功能" class="headerlink" title="十一、prettytable库打印表格美化输出功能"></a>十一、prettytable库打印表格美化输出功能</h1><pre class="line-numbers language-python"><code class="language-python"><span class="token keyword">from</span> prettytable <span class="token keyword">import</span> PrettyTable
t <span class="token operator">=</span> PrettyTable<span class="token punctuation">(</span><span class="token punctuation">[</span><span class="token string">'Params'</span><span class="token punctuation">,</span> <span class="token string">'Value'</span><span class="token punctuation">]</span><span class="token punctuation">)</span>
t<span class="token punctuation">.</span>add_row<span class="token punctuation">(</span><span class="token punctuation">[</span><span class="token string">"train"</span><span class="token punctuation">,</span><span class="token string">"train.txt"</span><span class="token punctuation">]</span><span class="token punctuation">)</span>
t<span class="token punctuation">.</span>add_row<span class="token punctuation">(</span><span class="token punctuation">[</span><span class="token string">"embedding"</span><span class="token punctuation">,</span><span class="token string">"20"</span><span class="token punctuation">]</span><span class="token punctuation">)</span>
<span class="token keyword">print</span><span class="token punctuation">(</span>t<span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;输出结果为：</p>
<p><img src="/Images/NERRUN/image-20210403155739965.png" alt="image-20210403155739965"></p>
<h1 id="十二、with-tf-session-as-sess"><a href="#十二、with-tf-session-as-sess" class="headerlink" title="十二、with tf.session() as sess"></a>十二、with tf.session() as sess</h1><p>session是TensorFlow中的对话。sess.run()中<strong>不能放tuple</strong>的值。<br>&emsp;&emsp;1、tensorflow可以提前定义很多变量和函数，但是这些操作不直接执行，要通过session run的形式才可以执行。<br>&emsp;&emsp;2、作用：session提供了operation执行和tensor求值的环境，有两种情况：<br> &emsp;&emsp;&emsp;&emsp;2.1 由于回话接受以后需要手动关闭，不然变量没有办法释放</p>
<pre class="line-numbers language-python"><code class="language-python"><span class="token keyword">import</span> tensorflow <span class="token keyword">as</span> tf
a <span class="token operator">=</span> tf<span class="token punctuation">.</span>constant<span class="token punctuation">(</span><span class="token number">4</span><span class="token punctuation">)</span>  <span class="token comment" spellcheck="true"># 定义一个常量a</span>
b <span class="token operator">=</span> tf<span class="token punctuation">.</span>constant<span class="token punctuation">(</span><span class="token number">7</span><span class="token punctuation">)</span>
c <span class="token operator">=</span> a<span class="token operator">*</span>b
sess <span class="token operator">=</span> tf<span class="token punctuation">.</span>Session<span class="token punctuation">(</span><span class="token punctuation">)</span>
<span class="token keyword">print</span><span class="token punctuation">(</span>sess<span class="token punctuation">.</span>run<span class="token punctuation">(</span>c<span class="token punctuation">)</span><span class="token punctuation">)</span>  <span class="token comment" spellcheck="true"># 输出张量值需用sess.run()</span>
sess<span class="token punctuation">.</span>close
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;&emsp;&emsp;输出结果为：28 </p>
<p>&emsp;&emsp;&emsp;&emsp;2.2 使用witth tf.session()创建上下文来执行，上下文退出时自动释放。<strong>注：若没有session的话，tensor的值为0，也不报错，如以下第一个输出。</strong></p>
<pre class="line-numbers language-python"><code class="language-python"><span class="token keyword">import</span> tensorflow <span class="token keyword">as</span> tf
a <span class="token operator">=</span> tf<span class="token punctuation">.</span>constant<span class="token punctuation">(</span><span class="token number">4</span><span class="token punctuation">)</span>
b <span class="token operator">=</span> tf<span class="token punctuation">.</span>constant<span class="token punctuation">(</span><span class="token number">7</span><span class="token punctuation">)</span>
c <span class="token operator">=</span> tf<span class="token punctuation">.</span>add<span class="token punctuation">(</span>a<span class="token punctuation">,</span>b<span class="token punctuation">)</span>
<span class="token keyword">print</span><span class="token punctuation">(</span><span class="token string">"直接输出两数之和c:"</span><span class="token punctuation">,</span>c<span class="token punctuation">)</span>
<span class="token keyword">with</span> tf<span class="token punctuation">.</span>Session<span class="token punctuation">(</span><span class="token punctuation">)</span> <span class="token keyword">as</span> sess<span class="token punctuation">:</span>
    <span class="token keyword">print</span><span class="token punctuation">(</span><span class="token string">"经过session run形式的两数之和C:"</span><span class="token punctuation">,</span>sess<span class="token punctuation">.</span>run<span class="token punctuation">(</span>c<span class="token punctuation">)</span><span class="token punctuation">)</span>
<span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span><span></span><span></span><span></span></span></code></pre>
<p>&emsp;&emsp;&emsp;&emsp;输出的结果为：<img src="/Images/NERRUN/image-20210403165909044.png" alt="image-20210403165909044"></p>
<p><img src="/Images/NERRUN/image-20210403165918814.png" alt="image-20210403165918814"></p>

                
            </div>
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